WhiteDataReader

c302/WhiteDataReader.py

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+# -*- coding: utf-8 -*-
+
+############################################################
+
+#    A simple script to read the values in herm_full_edgelist.csv.
+
+#    This is on of a number of interchangeable "Readers" which can 
+#    be used to get connection data for c302
+
+############################################################
+
+import csv
+
+from c302.NeuroMLUtilities import ConnectionInfo
+from c302.NeuroMLUtilities import analyse_connections
+import os
+
+from c302 import print_
+
+spreadsheet_location = os.path.dirname(os.path.abspath(__file__))+"/data/"
+filename = "%saconnectome_white_1986_A.csv" % spreadsheet_location
+
+def get_all_muscle_prefixes():
+    return ["pm", "vm", "um", "dBWM", "vBWM"]
+
+
+def get_body_wall_muscle_prefixes():
+    return ["dBWM", "vBWM"]
+
+
+def is_muscle(cell):
+    known_muscle_prefixes = get_all_muscle_prefixes()
+    return cell.startswith(tuple(known_muscle_prefixes))
+
+
+def is_body_wall_muscle(cell):
+    known_muscle_prefixes = get_body_wall_muscle_prefixes()
+    return cell.startswith(tuple(known_muscle_prefixes))
+
+
+def is_neuron(cell):
+    return cell[0].isupper()
+
+
+def remove_leading_index_zero(cell):
+    """
+    Returns neuron name with an index without leading zero. E.g. VB01 -> VB1.
+    """
+    if is_neuron(cell) and cell[-2:].startswith("0"):
+        return "%s%s" % (cell[:-2], cell[-1:])
+    return cell
+
+def get_old_muscle_name(muscle):
+    index = int(muscle[6:])
+    if index < 10:
+        index = "0%s" % index
+    if muscle.startswith("BWM-VL"):
+        return "MVL%s" % index
+    elif muscle.startswith("BWM-DR"):
+        return "MVR%s" % index
+    elif muscle.startswith("BWM-DL"):
+        return "MDL%s" % index
+    elif muscle.startswith("BWM-DR"):
+        return "MDR%s" % index
+
+def get_syntype(syntype):
+    if syntype == "electrical":
+        return "GapJunction"
+    elif syntype == "chemical":
+        return "Send"
+    else:
+        raise NotImplementedError("Cannot parse syntype '%s'" % syntype)
+
+def get_synclass(cell, syntype):
+    #dirty hack
+    if syntype == "GapJunction":
+        return "Generic_GJ"
+    else:
+        if cell.startswith("DD") or cell.startswith("VD"):
+            return "GABA"
+        return "Acetylcholine"
+
+def parse_row(row):
+    pre = str.strip(row["Source"])
+    post = str.strip(row["Target"])
+    num = int(row["Weight"])
+    syntype = get_syntype(str.strip(row["Type"]))
+    synclass = get_synclass(pre, syntype)
+    return pre, post, num, syntype, synclass
+
+def read_data(include_nonconnected_cells=False):
+    """
+    Args:
+        include_nonconnected_cells (bool): Also append neurons without known connections to other neurons to the 'cells' list. True if they should get appended, False otherwise.
+    Returns:
+        cells (:obj:`list` of :obj:`str`): List of neurons
+        conns (:obj:`list` of :obj:`ConnectionInfo`): List of connections from neuron to neuron
+    """
+
+    conns = []
+    cells = []
+
+    with open(filename, 'r') as f:
+        reader = csv.DictReader(f)
+        print_("Opened file: " + filename)
+
+        known_nonconnected_cells = ['CANL', 'CANR']
+
+        for row in reader:
+            pre, post, num, syntype, synclass = parse_row(row)
+
+            if not is_neuron(pre) or not is_neuron(post):
+                continue  # pre or post is not a neuron
+
+            pre = remove_leading_index_zero(pre)
+            post = remove_leading_index_zero(post)
+
+            conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
+            #print ConnectionInfo(pre, post, num, syntype, synclass)
+            if pre not in cells:
+                cells.append(pre)
+            if post not in cells:
+                cells.append(post)
+
+        if include_nonconnected_cells:
+            for c in known_nonconnected_cells:
+                if c not in cells:
+                    cells.append(c)
+
+    return cells, conns
+
+
+def read_muscle_data():
+    """
+    Returns:
+        neurons (:obj:`list` of :obj:`str`): List of motor neurons. Each neuron has at least one connection with a post-synaptic muscle cell.
+        muscles (:obj:`list` of :obj:`str`): List of muscle cells.
+        conns (:obj:`list` of :obj:`ConnectionInfo`): List of neuron-muscle connections.
+    """
+
+    neurons = []
+    muscles = []
+    conns = []
+
+    with open(filename, 'r') as f:
+        reader = csv.DictReader(f)
+        print_("Opened file: " + filename)
+
+        for row in reader:
+            pre, post, num, syntype, synclass = parse_row(row)
+
+            if not (is_neuron(pre) or is_body_wall_muscle(pre)) or not is_body_wall_muscle(post):
+                continue
+
+            if is_neuron(pre):
+                pre = remove_leading_index_zero(pre)
+            else:
+                pre = get_old_muscle_name(pre)
+            post = get_old_muscle_name(post)
+
+            conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
+            if is_neuron(pre) and pre not in neurons:
+                neurons.append(pre)
+            elif is_body_wall_muscle(pre) and pre not in muscles:
+                muscles.append(pre)
+            if post not in muscles:
+                muscles.append(post)
+
+    return neurons, muscles, conns
+
+
+def main():
+
+    cells, neuron_conns = read_data(include_nonconnected_cells=True)
+    neurons2muscles, muscles, muscle_conns = read_muscle_data()
+
+    analyse_connections(cells, neuron_conns, neurons2muscles, muscles, muscle_conns)
+
+if __name__ == '__main__':
+    main()